{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d885824b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from itertools import combinations\n",
    "\n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "\n",
    "import networkx as nx\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('fivethirtyeight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7a2494ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "COLORS = [\n",
    "    '#00B0F0',\n",
    "    '#FF0000'\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0fd06fd",
   "metadata": {},
   "source": [
    "# Chapter 01\n",
    "\n",
    "This chapter introduces the concept of causality and highlights similarities and differences between causal inference and statistical learning. A brief historical outline of the concept of causality is provided to help the reader understand a broader context. Finally, three motivating examples are provided (medicine, marketing, social policy) to demonstrate the importance of causal inference in terms of technical, practical and business perspectives. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6c49b0c",
   "metadata": {},
   "source": [
    "## Confounding "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "9db62153",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let's set random seed for reproducibility\n",
    "np.random.seed(45)\n",
    "\n",
    "# `b` represents our confounder\n",
    "b = np.random.rand(100)\n",
    "\n",
    "# `a` and `c` are causally independent of each other, but they are both children of `b` \n",
    "a = b + .1 * np.random.rand(100)\n",
    "c = b + .3 * np.random.rand(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "25652f3a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9627497625297509\n"
     ]
    }
   ],
   "source": [
    "# Let's check correlation between `a` and `c`\n",
    "coef, p_val = stats.pearsonr(a, c)\n",
    "\n",
    "print(coef)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "ac319993",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "variables = {\n",
    "    'a': a,\n",
    "    'b': b,\n",
    "    'c': c\n",
    "}\n",
    "\n",
    "plt.figure(figsize=(12, 7))\n",
    "\n",
    "for i, (var_1, var_2) in enumerate([('b', 'a'), ('b', 'c'), ('c', 'a')]):\n",
    "    \n",
    "    color = COLORS[1]\n",
    "    \n",
    "    if 'b' in [var_1, var_2]:\n",
    "        color = COLORS[0]\n",
    "    \n",
    "    plt.subplot(2, 2, i + 1)\n",
    "    plt.scatter(variables[var_1], variables[var_2], alpha=.8, color=color)\n",
    "    \n",
    "    plt.xlabel(f'${var_1}$', fontsize=16)\n",
    "    plt.ylabel(f'${var_2}$', fontsize=16)\n",
    "\n",
    "plt.suptitle('Pairwise relationships between $a$, $b$ and $c$')\n",
    "plt.subplots_adjust(hspace=.25, wspace=.25)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a1f0699b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:causal_book_py38]",
   "language": "python",
   "name": "conda-env-causal_book_py38-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
